Authors:
Sven Groppe
and
Jinghua Groppe
Affiliation:
Institute of Information Systems (IFIS), University of Lübeck, Ratzeburger Allee 160, D-23562 Lübeck, Germany
Keyword(s):
Databases, Multi-platform, Multi-model, Cloud, Post-cloud, Edge/fog/dew Computing, Hardware Acceleration, Internet-of-Things (IoT), Mobile Database, Parallel Database, Main-memory Database.
Abstract:
There exist various standards for different models of data, and hence users often must handle a zoo of data models. Storing and processing data in their native models, but spanning optimizations and processing across these models seem to be the most efficient way, such that we recently observe an advent of multi-model databases for this purpose. Companies, end users and developers typically run different platforms like mobile devices, web, desktops, servers, clouds and post-clouds (e.g., fog and edge computing) as execution environments for their applications at the same time. In this paper, we propose to utilize the different platforms according to their advantages and benefits for data distribution, query processing and transaction handling in an overall integrated hybrid multi-model multi-platform (HM3P) database. We analyze current state-of-the-art multi-model databases according to the support of multiple platforms. Furthermore, we analyze the properties of databases running on
different types of platforms. We detail new challenges for the novel concept of HM3P databases concerning a global optimization of data distribution, query processing and transaction handling across multiple platforms.
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